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Glama

LiveDataLink

by io.github.blackboxfoundry

paper_details

Read-onlyIdempotent

Get full catalog metadata for a single scholarly work by OpenAlex id (e.g. 'W2741809807') or DOI (e.g. '10.1038/nature12373'). Returns title, authors, venue, year, citation count, open-access status, and a free full-text URL when available. For a bare arXiv id, use paper_get_text with paper_key 'arxiv:' to read indexed text, or paper_search by title for OpenAlex metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesOpenAlex id ('W...') or DOI ('10.x/...'). For arXiv ids, use paper_get_text or paper_search instead.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already convey readOnly/idempotent/non-destructive behavior. The description adds useful behavioral detail by enumerating the returned fields (title, authors, venue, year, citation count, open-access status, full-text URL when available), including a conditional. Only minor behaviors such as not-found handling are left unstated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences each serve a distinct purpose: core operation, return content, and alternative-tool routing. No redundant or filler text; the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter lookup tool with no output schema, the description covers accepted inputs, return fields, and the one likely misrouting case (bare arXiv IDs). An agent has enough to select and invoke the tool correctly without inspecting related tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single id parameter is fully documented in the schema (OpenAlex ID or DOI, arXiv exclusion), and schema coverage is 100%. The description reinforces this with concrete examples and alternative routing, but does not add substantial new parameter meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Get'), resource ('full catalog metadata for a single scholarly work'), and accepted identifiers (OpenAlex ID or DOI). It also names alternatives for arXiv IDs, distinguishing paper_details from paper_get_text and paper_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells the agent when paper_details is appropriate (given an OpenAlex ID or DOI) and when to switch to paper_get_text or paper_search for bare arXiv IDs. This is clear routing guidance beyond the schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.

Resources